About

NLDB(capitals denote Natural Ligand DataBase;
URL: http://nldb.hgc.jp) is a database of automatically corrected and
predicted 3D protein-ligand interactions in the enzymatic reactions of
various metabolic pathways. Information about such non-covalent
interactions is important, not only for studying the molecular functions
of specific proteins but also for enzyme-targeted drug discovery, and
thus it will be valuable to complement the structural information about
the reactions obtained by computational approaches. Therefore, we
predict 3D protein-ligand interactions using reliable, state-of-the-art
software programs if their complex structures are unknown, and then
construct a database of the 3D interactions in various
enzymatic reactions.

NLDB produces three different types of data resources, natural, analog, and ab initio complex
structures. The natural complexes are experimentally determined
protein-ligand complex structures in the PDB, the analog complexes are
predicted based on known protein structures in a complex with a similar
ligand (analog) by transforming a target ligand to the analog using the
fkcombu program in KCOMBU [1], and the ab initio complexes are predicted
by docking a ligand to predicted or high confidence ligand-binding
sites of a protein using AutoDock VINA [2]. In addition, the
ligand-binding sites of protein are predicted using BUMBLE [3]
and the high confidential binding sites of a protein are
obtained by mapping ligand-binding sites among homologous
proteins. Furthermore, the database has a
flexible search function, based on various types of relevant keywords,
and an enrichment analysis function based on a set of KEGG compound IDs.

NLDB will be a valuable resource for experimental biologists studying
protein-ligand interactions in specific chemical reactions, and for
theoretical researchers wishing to undertake more precise simulations of
interactions for drug discovery purposes. NLDB is freely accessible at
http://nldb.hgc.jp, and will be regularly updated every three months

VaProS, VAriation effect on PROtein Structure and function, is a new data cloud for
Structural Life Science and is the core technology to lead the collaboration between
the discipline in Structural Biology and the whole Life Sciences.